Resume

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Professional Experience

Apple
Manufacturing - ML Embedded Systems
August 2025 - Present | Cupertino, CA

Ford Motor Company
Intern Technical Product Manager AI-ML
May 2025 – August 2025 | Palo Alto, CA

  • Drove requirements for a cross-functional collaboration with 40+ ML engineers and UX teams to deliver an executive demo prototype evaluating embedded and cloud AI LLM and SLM models, influencing a $200M+ third-party contract.
  • Led development and rollout of a custom language model with cloud fallback enabling real-time, context-aware interactions using CAN bus data.
  • Defined and implemented retrieval-augmented generation (RAG)-based KPIs and performance metrics in BigQuery, enabling continuous data-driven product iterations and informed roadmap prioritization.
  • Coordinated agile ceremonies and backlog prioritization to accelerate delivery while balancing stakeholder input from technical and business teams.

Ford Motor Company
Intern Data Science
May 2024 – August 2024 | Palo Alto, CA

  • Integrated Vehicle Energy Model into Android Auto across 20,000+ E-Transit vans, improving energy-aware routing and contributing to enhanced user experience for fleet drivers.
  • Automated hyperparameter tuning workflows across diverse EV usage scenarios, boosting State of Charge (SOC) prediction accuracy by 18%, leading to improved route planning reliability.
  • Collaborated with Apple CarPlay UX and SYNC teams to refine EV pairing and routing experiences for over 200,000 vehicles, incorporating user feedback to optimize usability.

Education

Harvey Mudd College
Claremont, CA
Bachelor of Science, Engineering & Economics
May 2026

  • Product Place, Advanced Rocketry, Robotics, Varsity Track (100m SCIAC Champion), Dean’s List

Carnegie Mellon University
Pittsburgh, PA
Technical Degree, Design
August 2021

Projects

Abercrombie & Fitch — ML Personalization Engine for Spotify Campaign
Finalist

  • Designed and launched an ML-powered personalization engine using clustering and collaborative filtering, increasing campaign engagement through targeted content delivery.
  • Led multivariate A/B testing and iterative model refinement, driving improved viral content conversion and campaign ROI.

Generative AI Systems — Databricks Lakehouse

  • Built and integrated SQL/Python tools with an LLM custom agent for product Q&A, leveraging Unity Catalog for governance.
  • Evaluated and refined agent performance using MLflow GenAI.

Skills

Product & Strategy

  • Agile (JIRA, Asana), A/B Testing, Roadmapping, User Research
  • Data-Driven Decision Making, Stakeholder Management

Technical

  • Python, SQL, BigQuery, TensorFlow, Protobuf, CAN/LIN
  • Android Auto, Retrieval-Augmented Generation (RAG), SLMs
  • NLU + LLM, Node.js

Tools

  • GitHub, Figma, Unity Catalog, Protopie, Cursor